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Kimi K2 0711

Added Jan 1, 2024Open weights

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Kimi K2 0711 version. Kimi-k2 is a Mixture-of-Experts (MoE) foundation model with exceptional coding and agent capabilities, featuring 1 trillion total parameters and 32 billion activated parameters. In benchmark evaluations covering general knowledge reasoning, programming, mathematics, and agent-related tasks, the K2 model outperforms other leading open-source models. Quantized at FP8.

  • Tools
Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.40
Output
$1.80

Reference prices as published by the model provider. API example

Specifications

Context window
128K
Max output
8.2K
Average output (7 days)
735 tokens
Longer than 63% of 465 models

Side by side

Kimi K2 0711 compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Kimi K2 0711MoonshotThis modelKimi K3MoonshotRemove
ProviderMoonshotMoonshot
Discovery tierOpen weightsOpen weights
AddedJan 1, 2024Jul 16, 2026
Limits
Context window128K1.05MBest
Max output8.19K—
Average output735 tokens1.1K tokens
Pricing, USD per 1M tokens
Input$0.40Best$1.20
Output$1.80Best$5.50
Cache read—$0.20
Performance
Throughput—151.2 tok/s
Time to first token—2.9 s
Request success (24h)—99.9%
Benchmark indexes
Intelligence Index12.743.6Best
Coding Index—76.2
Math Index57.0—
Capabilities
ReasoningNoYes
ToolsYesYes
VisionNoYes
Structured outputNoYes
Video inputNoYes
Reasoning effort—low, high, max

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Kimi K2 0711
  • Kimi K3

Intelligence Index

  • Kimi K2 071112.7
  • Kimi K343.6

Kimi K2 0711: Better than 28% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Kimi K2 0711: —
    • Kimi K3: 76.2

  • Math Index

    Composite of the math evaluations

    • Kimi K2 0711: 57.0
    • Kimi K3: —

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Kimi K2 0711: —
    • Kimi K3: 58.3%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Kimi K2 0711: —
    • Kimi K3: 24.8%

  • Harvey LAB-AAv1.1

    Legal tasks passed in full, with no material hallucination

    • Kimi K2 0711: —
    • Kimi K3: 5.3%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Kimi K2 0711: —
    • Kimi K3: 1,499 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Kimi K2 0711: —
    • Kimi K3: 1,534 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Kimi K2 0711: —
    • Kimi K3: 22.0%

  • AA-LCRv1.1

    Reasoning across long documents

    • Kimi K2 0711: 53.0%
    • Kimi K3: 88.7%Top

  • MLCR-AA

    Long-context reasoning over medical records

    • Kimi K2 0711: —
    • Kimi K3: 21.7%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Kimi K2 0711: 7.4%
    • Kimi K3: 46.9%Top

  • GPQA Diamond

    Graduate-level science questions

    • Kimi K2 0711: 76.6%
    • Kimi K3: 93.5%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Kimi K2 0711: 82.4%
    • Kimi K3: —

  • IFBench

    Following precise output instructions

    • Kimi K2 0711: 41.5%
    • Kimi K3: —

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Kimi K2 0711: —
    • Kimi K3: 12.6%

  • SciCode

    Scientific computing in Python

    • Kimi K2 0711: —
    • Kimi K3: 59.5%

  • LiveCodeBench

    Recent competitive programming problems

    • Kimi K2 0711: 55.6%
    • Kimi K3: —

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Kimi K2 0711: 57.0%
    • Kimi K3: —

  • AIME

    Competition mathematics

    • Kimi K2 0711: 69.3%
    • Kimi K3: —

  • MATH-500

    Competition math problems

    • Kimi K2 0711: 97.1%
    • Kimi K3: —

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Kimi K2 0711: 15.9%
    • Kimi K3: —

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Kimi K2 0711: 61.1%
    • Kimi K3: —

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Kimi K2 0711: 53.0%
    • Kimi K3: 88.7%Top

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "moonshotai/kimi-k2-instruct-0711",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="moonshotai/kimi-k2-instruct-0711",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Moonshot

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